• Energy Research

This paper proposes an energy management scheme to maximize the use of solar energy in the smart grid. In this context, a shared facility controller (SFC) with a number of solar photovoltaic (PV) panels in a smart community is considered that has the capability to schedule the generated energy for consumption and trade to other entities. Particularly, a mechanism is designed for the SFC to decide on the energy surplus, if there is any, that it can use to charge its battery and sell to the households and the grid based on the offered prices. In this regard, a hierarchical energy management scheme is proposed with a view to reduce the total operational cost to the SFC. The concept of a virtual cost (VC) is introduced that aids the SFC to estimate its future operational cost based on some available current information. The energy management is conducted for three different cases and the optimal cost to the SFC is determined for each case via the theory of maxima and minima. A real-time algorithm is proposed to reach the optimal cost for all cases and some numerical examples are provided to demonstrate the beneficial properties of the proposed scheme. Journal paper

Global warming, and the resultant climate change, has become an urgent global issue. One potential partial solution to this problem and the focus of this paper is to design energy management mechanisms for buildings that encourage users’ acceptance of the technology for increased environmental sustainability. Particularly, this paper focuses on the design of an energy management technique for the air-conditioning (AC) systems in residential buildings that considers users’ views on how they use such technology. Note that while a large number of energy management mechanisms are available in the literature for ACs, most of these studies, however, do not consider how well the users may accept their use in the building. To address this issue, this paper first synthesizes some motivational psychology literature to understand users’ attitudes toward adopting such management techniques for the ACs within the building. Then, the obtained insights from various motivational models are incorporated into the design of an energy management scheme that encourages consumers to accept the technology that reduces electricity consumption, the cost of electricity, peak power from the grid; and the generation of CO2 in the residential building. Finally, some experimental results are provided to illustrate how the designed energy management mechanism validates the motivational psychology models in terms of providing various benefits to the users, and thus shows the potential of being accepted by them.

In this paper, we investigate the factors that influence the customer's decision in subscribing to a particular demand response management (DRM) scheme. Based on these factors, we suggest a classification of customer types that include non-green comfort seeking behavior (NCSB) and green incentive seeking behavior (GISB). We use multi-tier DRM plans that clearly specify the incentive and inconvenience for NCSB and GISB customers. The grid operator can obtain maximum profit margin (after paying out the incentives to participating users) from the DRM only if a specific number of customers participate in the NCSB and GISB plans. Any deviation from an ideal subscription pattern is undesirable from the grid's perspective. We also develop a mathematical framework that is based on logistic regression and considers the quantifiable as well as unquantifiable attributes of customer behavior. This model captures the probabilistic nature of customer preferences for different DRM plans. Simulation results reveal that the actual subscription of customers in NCSB and GISB plans significantly deviates from the ideal values. From these, we determine a compromise solution that lies between the ideal and the actual solutions. We also identify that along with economic factors, social factors, such as peer pressure and prompting green or caring behavior, could also be used as potential tools by the grid operator to influence the customer preference. This paper can also be used by the grid operator to design appropriate multi-tier DRM plans.

In this paper, the feasibility of peer-to-peer (P2P) energy trading in a voltage-constrained grid-connected network is studied. In particular, a local voltage management scheme is proposed that takes network constraints into consideration to instruct the prosumers to trade energy frequently in the P2P market. A coalition graph game-based P2P energy trading framework is developed, in which prosumers can form the coalition to negotiate and decide on the energy trading parameters, such as trading quantities and prices. The Myerson value rule is used to allocate the total payoff of the proposed game fairly among the participating prosumers. Further, the stability of the proposed coalition structure is confirmed. Several simulation results are provided to verify the effectiveness of the developed P2P trading model. The simulation results show that the proposed P2P trading framework can enable prosumers to export power without causing high voltage problem in the network, and help prosumers cut down a significant portion of their overall electricity costs compared to the feed-in-tariff and coalition game model without mutual negotiations.

Successful deployment of smart grids necessitates experimental validities of their state-of-the-art designs in two-way communications, real-time demand response and monitoring of consumers' energy usage behavior. The objective is to observe consumers' energy usage pattern and exploit this information to assist the grid in designing incentives, energy management mechanisms, and real-time demand response protocols; so as help the grid achieving lower costs and improve energy supply stability. Further, by feeding the observed information back to the consumers instantaneously, it is also possible to promote energy efficient behavior among the users. To this end, this paper performs a literature survey on smart grid testbeds around the world, and presents the main accomplishments towards realizing a smart grid testbed at the Singapore University of Technology and Design (SUTD). The testbed is able to monitor, analyze and evaluate smart grid communication network design and control mechanisms, and test the suitability of various communications networks for both residential and commercial buildings. The testbeds are deployed within the SUTD student dormitories and the main university campus to monitor and record end-user energy consumption in real-time, which will enable us to design incentives, control algorithms and real-time demand response schemes. The testbed also provides an effective channel to evaluate the needs on communication networks to support various smart grid applications. In addition, our initial results demonstrate that our testbed can provide an effective platform to identify energy wastage, and prompt the needs of a secure communications channel as the energy usage pattern can provide privacy related information on individual user. 2016

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes. 38 pages, single column, double space